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Neuratel-AI

Neuratel MCP Server

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by Neuratel-AI
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Python
Remote

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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.9/5.0

    Scored across 46 tools

    Disambiguation4/5

    Tools are organized by resource (calls, campaigns, agents, numbers, DNC, knowledge bases, webhooks, conversations, analytics) with clear role separation. Minor overlap exists between analytics tools (get_usage, get_chat_analytics, get_combined_analytics) and between call history tools (get_active_calls, list_calls, get_call), but descriptions provide sufficient differentiation.

    Naming Consistency5/5

    Nearly all tools follow a consistent verb_noun pattern (create_agent, list_agents, update_agent, start_campaign, pause_campaign, dnc_add_entry). The few exceptions like add_knowledge_from_text and get_agent_required_variables are still descriptive and follow a noun+preposition style that doesn't create confusion.

    Tool Count2/5

    46 tools is a very large surface for a single server. Even for a broad voice AI platform, the count exceeds the practical threshold for agent tool selection and suggests opportunities to consolidate related operations (e.g., separate DNC tools, separate conversation tools, multiple analytics tools).

    Completeness3/5

    The server covers core voice/call, agent lifecycle, campaign management, DNC compliance, and conversation messaging well. However, there are missing lifecycle endpoints: campaigns cannot be updated or deleted (only paused/stopped), knowledge bases cannot be deleted or detached individually, and webhooks lack update/delete operations. These gaps create dead ends for management workflows.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

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